Image Classification On Svhn

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Percentage error

평가 결과

이 벤치마크에서 각 모델의 성능 결과

		Paper Title	Repository
KNN	77.93	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
TSVM	66.55	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
M1+KNN	65.63	Semi-Supervised Learning with Deep Generative Models
M1+TSVM	54.33	Semi-Supervised Learning with Deep Generative Models
M1+M2	36.02	Semi-Supervised Learning with Deep Generative Models
DGN	36.02	Semi-Supervised Learning with Deep Generative Models
Supervised CNN	28.87	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Auxiliary DGN	22.86	Auxiliary Deep Generative Models	-
DCGAN	22.48	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Skip DGN	16.61	Auxiliary Deep Generative Models	-
ANODE	16.5	Augmented Neural ODEs
SEER (RegNet10B)	13.6	Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Sign-symmetry	10.16	How Important is Weight Symmetry in Backpropagation?
Local Mixup LeNet	8.20	Preventing Manifold Intrusion with Locality: Local Mixup
Improved GAN	8.11	Improved Techniques for Training GANs
CLS-GAN	5.98	Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities
Convolutional neural networks applied to house numbers digit classification	4.9	-	-
FLSCNN	4.0	Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network	-
Deep Complex	3.3	Deep Complex Networks
Stochastic Pooling	2.8	Stochastic Pooling for Regularization of Deep Convolutional Neural Networks

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Image Classification On Svhn

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평가 결과